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Dr Richard Everitt has recently been awarded funding from NERC for a project on inference for complex process-based decision making for UK land asset use

The Statistics Department has recently been awarded funding from NERC for the project "Statistical inference and uncertainty quantification for complex process-based models using multiple data sets". Principal Investigator Richard Everitt, will collaborate on the project with other members of the Department (Rito Dutta, Christian Robert and Martyn Plummer), the Ecology group at the University of Reading, and with the Centre for Environment, Fisheries and Aquaculture Science.

Making responsible decisions about landscapes is facilitated by the use of complex models able to represent multiple competing demands on land use. Decisions about land use require that trade-offs between competing demands be identified, and their consequences through time be characterised. Models consisting of stochastic computer simulations are increasingly used to make realistic predictions about real world processes from socio-ecological systems involving land use. dels attempt to simulate all relevant aspects of a real physical system, they may involve many parameters, some of which will be difficult to set correctly. The final objective of these models is to assess the possible consequences of management decisions, such as the placement of wind turbines, thus it is crucially important that the uncertainty introduced by calibrating parameter values be understood.

In order to make informed decisions, one needs to be able to consider the effects of a number of complex interacting temporal and spatial processes (e.g. hydrological, ecological, agricultural, economic, climate). The project will develop new techniques in Approximate Bayesian Computation to enable parameter estimation for models for these processes, taking into account the impact of model misspecification. This project is part of the Strategic Priorities Fund on Landscape Decisions. https://landscapedecisions.org/

Tue 16 Jun 2020, 11:24 | Tags: Dept, Faculty of Science

Professor Chenlei Leng elected Fellow of the IMS

Chenlei Leng, Professor of Statistics, University of Warwick, has been named Fellow of the Institute of Mathematical Sciences (IMS). Professor Leng received the award for fundamental contributions to the theory and practice of high dimensional statistics, statistical machine learning, model selection and network data analysis.

Created in 1935, the Institute of Mathematical Sciences is a member organisation that fosters the development and dissemination of the theory and applications of statistics and probability. The IMS has 3,500 active members throughout the world.

https://imstat.org/2020/05/19/ims-names-2020-fellows/

Tue 26 May 2020, 11:13 | Tags: Dept, Science, Faculty of Science

Warwick Statistics Professor to provide COVID-19 Intervention Modelling for East Africa (CIMEA)

Professor Xavier Didelot is a member of a team of Warwick researchers awarded a £1m grant from the Wellcome Trust to work with East African countries in their emergency preparations for COVID-19 as the pandemic spreads across Africa.

https://warwick.ac.uk/newsandevents/pressreleases/warwick_researchers_to/

Thu 14 May 2020, 09:31 | Tags: Dept, Science, Faculty of Science


Tom Berrett wins RSS research prize

Congratulations to Tom Berrett on being awarded the Royal Statistical Society Research Prize . The citation notes his outstanding contributions to understanding and developing nearest neighbour methods for classification, entropy and related functional estimation, and his highly original work on independence and conditional independence testing. Tom will join the Department of Statistics in July.
https://www.statslife.org.uk/news/4453-announcing-our-honours-recipients-for-2020

Thu 05 Mar 2020, 14:08 | Tags: Dept, Faculty of Science

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